Will It Run AI

Can Granite 4.1 30B run on NVIDIA A40 48GB?

YES — Runs Great

A83Great
Estimated from fit model

Granite 4.1 30B needs ~28.2 GB VRAM. NVIDIA A40 48GB has 48.0 GB. With Q4_K_M quantization, expect ~30 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: BasicBottleneck: Balanced
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Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) 28.2 GB, 31.9 tok/s, Runs well
28.2 GB required48.0 GB available
59% VRAM used

Fit status

Runs well

Decode

31.9 tok/s

TTFT

6071 ms

Safe context

97K

Memory

28.2 GB / 48.0 GB

Memory breakdown

Weights18.3 GB
KV Cache3.9 GB
Runtime1.2 GB
Headroom4.8 GB

See how fast it feels

See how fast it feelsGranite 4.1 30B on NVIDIA A40 48GB
1st promptCold start — includes initialization
>Write a Python function to sort a list
Here's a Python function that sorts a list using quicksort: def quicksort(arr): if len(arr) <= 1: return arr pivot = arr[len(arr) // 2] left = [x for x in arr if x < pivot] middle = [x for x in arr if x == pivot] right = [x for x in arr if x > pivot] return quicksort(left) + middle + quicksort(right) # Example usage numbers = [3, 6, 8, 10, 1, 2, 1] print(quicksort(numbers)) # [1, 1, 2, 3, 6, 8, 10] The algorithm picks a pivot, partitions the list into smaller, equal, and larger elements, then recursively sorts each partition and concatenates the results.
2nd promptWarm — model ready, no init overhead
>Now add type hints and a docstring
def quicksort(arr: list[int]) -> list[int]: """Sort a list using the quicksort algorithm. Args: arr: List of integers to sort. Returns: A new sorted list. """ if len(arr) <= 1: return arr pivot = arr[len(arr) // 2] left = [x for x in arr if x < pivot] middle = [x for x in arr if x == pivot] right = [x for x in arr if x > pivot] return quicksort(left) + middle + quicksort(right) Added type hints for the input and return type, plus a Google-style docstring.
Estimated: 31.9 tok/s decode · 6.1s TTFT (warm) · 80 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns well31.9 tok/s3311 ms97K
CodingARuns well29.7 tok/s6526 ms97K
Agentic CodingSRuns well31.9 tok/s8830 ms97K
ReasoningARuns well31.9 tok/s7175 ms97K
RAGSRuns well31.9 tok/s11038 ms97K

Quantization options

How Granite 4.1 30B (30B params) fits at each quantization level on NVIDIA A40 48GB (48.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
11.7 GB
LowA76
Q3_K_S
3
14.7 GB
LowA77
NVFP4
4
16.8 GB
MediumA77
Q4_K_M
4
18.3 GB
MediumA78
Q5_K_M
5
21.6 GB
HighA79
Q6_K
6
24.6 GB
HighA80
Q8_0Best for your GPU
8
32.1 GB
Very HighA80
F16
16
61.5 GB
MaximumF0

Get started

Copy-paste commands to run Granite 4.1 30B on your machine.

Run

ollama run granite4.1:30b

Your hardware

More models your NVIDIA A40 48GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS82.1 tok/s
AlibabaQwen 3.6 35B A3B35BS69 tok/s
AlibabaQwen 3.5 35B A3B35BS75 tok/s
AlibabaQwen 3 32B32BS30.2 tok/s
AlibabaQwen 3 30B A3B30.5BS82.1 tok/s

Frequently asked questions

Can NVIDIA A40 48GB run Granite 4.1 30B?

Yes, NVIDIA A40 48GB can run Granite 4.1 30B with a A grade (Runs well). Expected decode speed: 29.7 tok/s.

How much VRAM does Granite 4.1 30B need?

Granite 4.1 30B (30B parameters) requires approximately 28.2 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite 4.1 30B?

The recommended quantization for Granite 4.1 30B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite 4.1 30B run at on NVIDIA A40 48GB?

On NVIDIA A40 48GB, Granite 4.1 30B achieves approximately 29.7 tokens per second decode speed with a time-to-first-token of 6526ms using Q4_K_M quantization.

Can NVIDIA A40 48GB run Granite 4.1 30B for coding?

For coding workloads, Granite 4.1 30B on NVIDIA A40 48GB receives a A grade with 29.7 tok/s and 97K context.

What context window can Granite 4.1 30B use on NVIDIA A40 48GB?

On NVIDIA A40 48GB, Granite 4.1 30B can safely use up to 97K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for NVIDIA A40 48GBSee all hardware for Granite 4.1 30B
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